Resistance to chemotherapy and hormone therapy in endometrial cancer
Bibliographic record
Abstract
Endometrial cancer is the most common gynecological malignancy in developed countries and represents the eighth leading cause of cancer related death in women. The growing incidence of endometrial cancer leads scientists and oncologists to identify effective preventive measures and also molecular markers for diagnosis and prognosis. Chemotherapy and hormone therapy is the mainstay treatment option for advanced and recurrent endometrial cancer and response to therapy is one of the most important factor which favors prognosis and overall survival. In recent years, there have been major advances in the treatment of patients with endometrial cancer. Despite advances made in the treatment of this cancer, the overall survival of patients has not significantly improved because considerable number of patients harbor tumor refractory to these therapies and the majority of the initially responsive tumors become refractory to treatments. Therefore, determination of sensitivity/resistance is becoming increasingly important for individualization of endometrial cancer therapy. The aim of this review is to present the existing knowledge about the molecular markers that could play a crucial role in determining resistance to chemo- and hormone therapy. Extensive literature search for the cell signaling pathways and factors responsible for chemoresistance have been performed and reviewed. Several recent studies suggest that deregulations in the apoptotic pathways (such as p53, Fas/FasL, Bcl-2 family proteins, inhibitor of apoptosis proteins), survival pathways (PI3K/AKT, MAPK), hormone receptor signaling pathways (progesterone receptor), Cyclooxygenase-2 and Her-2 are considered as key factors involved in the onset and maintenance of therapeutic resistance, suggesting that resistance is a multi-factorial phenomenon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".